Antidepressants in Spine Surgery: A Systematic Review to Determine Benefits and Risks
Bibliographic record
Abstract
Antidepressant drugs can be advantageous in treating psychiatric and non-psychiatric illnesses, including spinal disorders. However, spine surgeons remain unfamiliar with the advantages and disadvantages of the use of antidepressant drugs as a part of the medical management of diseases of the spine. Our review article describes a systematic method using the PubMed/Medline database with a specific set of keywords to identify such benefits and drawbacks based on 17 original relevant articles published between January 2000 and February 2018; this provides the community of spine surgeons with available cumulative evidence contained within two tables illustrating both observational (10 studies; three cross-sectional, three case-control, and four cohort studies) and interventional (seven randomized clinical trials) studies. While tricyclic antidepressants (e.g., amitriptyline) and duloxetine can be effective in the treatment of neuropathic pain caused by root compression, venlafaxine may be more appropriate for patients with spinal cord injury presenting with depression and/or nociceptive pain. Despite the potential associated consequences of a prolonged hospital stay, higher cost, and controversial reports regarding the lowering of bone mineral density in the elderly, antidepressants may improve patient satisfaction and quality of life following surgery, and reduce postoperative pain and risk of delirium. The preoperative treatment of preexisting psychiatric diseases, such as anxiety and depression, can improve outcomes for patients with spinal cord injury-related disabilities; however, a preoperative platelet function assay is advocated prior to major spine surgical procedures to protect against significant intraoperative blood loss, as serotonergic antidepressants (e.g., selective serotonin reuptake inhibitors) and bupropion can increase the likelihood of bleeding intraoperatively due to drug-induced platelet dysfunction. This comprehensive review of this evolving topic can assist spine surgeons in better understanding the benefits and risks of antidepressant drugs to optimize outcomes and avoid potential hazards in a spine surgical setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".